Spark 1.5.2.
在 2015-11-26 13:19:39，"张志强(旺轩)" <zzq98...@alibaba-inc.com> 写道： What’s your spark version? 发件人: wyphao.2007 [mailto:wyphao.2...@163.com] 发送时间: 2015年11月26日 10:04 收件人: user 抄送:dev@spark.apache.org 主题: Spark checkpoint problem I am test checkpoint to understand how it works, My code as following: scala> val data = sc.parallelize(List("a", "b", "c")) data: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at parallelize at <console>:15 scala> sc.setCheckpointDir("/tmp/checkpoint") 15/11/25 18:09:07 WARN spark.SparkContext: Checkpoint directory must be non-local if Spark is running on a cluster: /tmp/checkpoint1 scala> data.checkpoint scala> val temp = data.map(item => (item, 1)) temp: org.apache.spark.rdd.RDD[(String, Int)] = MapPartitionsRDD[3] at map at <console>:17 scala> temp.checkpoint scala> temp.count but I found that only the temp RDD is checkpont in the /tmp/checkpoint directory, The data RDD is not checkpointed! I found the doCheckpoint function in the org.apache.spark.rdd.RDD class: private[spark] def doCheckpoint(): Unit = { RDDOperationScope.withScope(sc, "checkpoint", allowNesting = false, ignoreParent = true) { if (!doCheckpointCalled) { doCheckpointCalled = true if (checkpointData.isDefined) { checkpointData.get.checkpoint() } else { dependencies.foreach(_.rdd.doCheckpoint()) } } } } from the code above, Only the last RDD(In my case is temp) will be checkpointed, My question : Is deliberately designed or this is a bug? Thank you.
